ADWEC uses @RISK to help forecast Abu Dhabi’s water demand up until the year 2030.
The Abu Dhabi Water & Electricity Company (ADWEC) is a private joint stock company duly organised under the Law of the Emirate of Abu Dhabi pursuant to the 1998 Water & Electricity Law No.2 as a wholly owned subsidiary of the Abu Dhabi Power Corporation which is wholly owned by the Abu Dhabi Water and Electricity Authority (ADWEA).
ADWEC is the ‘Single Buyer and Seller’ of power and water in the Emirate of Abu Dhabi. It has to balance demand and supply through sales contracts on the basis of a Bulk Supply Tariff (BST) with the distribution companies and through Power and Water Purchase Agreements (PWPAs) with the generation companies. Its role is to guarantee the security and supply of water and electricity across the region.
Abu Dhabi relies almost completely on desalinated seawater for its potable water requirements. The desalination process is challenging in terms of operation, costs, and environmental impact. ADWEC must therefore forecast as accurately as possible the demand for water and electricity across the Emirate in order to plan for the optimum expansion as well as the most efficient and effective use of water production plants.
By undertaking risk analysis of the variables involved in assessing demand and supply, ADWEC minimises the potential for water production capacity to be over or under installed. Whilst over-production capacity is expensive, at the other end of the scale it is essential that Abu Dhabi has sufficient water production capacity to support the Abu Dhabi government development plan (Abu Dhabi Plan 2030).
@RISK determines water demand
ADWEC must allow for all feasible uncertainties in the variables that determine the quantity of water required over specific timescales. Before the implementation of @RISK, it used to prepare a high, an average, and a low water demand forecast scenario to do this. However, since 2006, it has been required by the Regulation and Supervision Bureau (RSB), the regulatory body of Abu Dhabi, to use a probabilistic approach and risk-based methodology to assess the water demand and the required capacity.
The RSB suggested implementing risk analysis software to achieve this, and ADWEC selected @RISK from Palisade because it offered the features it required and was cost-effective.
ADWEC now uses @RISK to help it forecast Abu Dhabi’s water demand up until the year 2030. (This timescale is in line with the government’s vision, ‘Abu Dhabi Plan 2030’, a framework to optimise the city’s development, based on environmental, social and economic criteria).
On the water demand side, the variables input into the @RISK model are based on the water demand categories such as domestic, agricultural and industrial. Each of these has its own set of data, assumptions and uncertainties, and ADWEC uses these to combine a bottom-up approach with @RISK’s statistical modelling tools to obtain the forecast that it requires to supply the right amount of water.
Factors with inherent uncertainties that affect the demand forecast outcome and are modelled by @RISK include: seasonal variation, distillers unplanned outages, water losses, population growth rates, and demand for housing.
As a result of using @RISK to assist with its forecasting, planning and management strategies, ADWEC has been able to consistently meet with almost complete accuracy and a high degree of confidence the Abu Dhabi Emirate water demand forecasts. It is keen to maintain this track record, which has contributed to Abu Dhabi being one of the few countries in the world that has had no water and electricity capacity shortages since 1998.
Head of Water Forecasting, ADWEC Planning and Studies Directorate
Key software features useful to ADWEC:
*Easily selected probability distribution curves *Improved reporting capabilities *Wide ranging capability of software *Ease of using data for other software, such as Palisade’s PrecisionTree
Specific techniques used by ADWEC for quantitative analysis ADWEC tries to limit the uncertainty band to a reasonable width otherwise it can become inconclusive. This is achieved through careful analysis of data and what to include and exclude.
Distributions used In population related analysis the normal distribution is used most commonly because this is the most representative. Other distributions can also be used depending on the data available, and the experience of the user.
Example snapshot The two charts below are samples of @RISK output. The first chart represents the demand forecast from year 2010 till 2030 for the Abu Dhabi Emirate including the water exports to neighbouring Emirates. It shows the most likely (mean) demand curve as well as the demand percentile bands above and below it.
The second chart represents the resultant demand probability distribution curve for year 2010. The charts have been produced using Monte Carlo simulation with just 100 iterations; sufficient for demonstration purposes. The model can be run with 10,000 iterations that result in smoother-edged curves.